New SAS Visual Analytics To Analyse And Visualise Big Data

SAS has introduced its new in-memory business intelligence (BI) solution, SAS Visual Analytics. The solution uses a highly visual interface to bring powerful analytics to a broader class of users. With this newest addition in the SAS High-Performance Analytics family organisations can analyse and visualise big data, visually explore data at the speed of sight, and share fresh insights with everyone, everywhere, via the Web or iPad.

SAS Visual Analytics combines the industry’s leading analytics, unique in-memory architecture, intuitive data exploration, Hadoop support and information-delivery options, including the iPad.

“The speed of in-memory architecture offers tremendous benefit. Organisations can explore huge data volumes and get answers to critical questions in near-real time,” said Dan Vesset, Program Vice President of IDC’s business analytics research.

“SAS Visual Analytics helps business users to visually explore data on their own,” said SAS CEO Jim Goodnight. “But it goes well beyond traditional query and reporting. Running on low-cost, industry-standard blade servers, its high-performance in-memory architecture delivers answers in seconds or minutes instead of hours or days,” he added.

A core component of SAS Visual Analytics, the SAS LASR Analytic Server, uses Hadoop (embedded Hadoop Distributed File System) as local storage at the server for fault tolerance. SAS LASR Analytic Server has been tested on billions of rows of data and is extremely scalable, bypassing the known column limitations of many relational database management systems (RDBMS).

The server components run on Red Hat or SUSE Linux, and the mobile client is available for the iPad from the iTunes® App Store. Other mobile devices will be supported in the future.

While the high end is not limited, SAS LASR Analytic Server reference configurations begin with an eight-blade server with 96 processor cores, 768 gigabytes memory and 4.8 terabytes (TB) of disk storage. The upper end of the reference configurations is 96 blades with 1,152 cores, 9.2 TB memory and 57.6 TB of disk storage, enough disk space to store the entire Library of Congress six times.